SegT一个实用的藏文分词系统

在分析现有藏文分词方法的基础上,该文重点研究了藏文分词中的格助词分块、临界词识别、词频统计、交集型歧义检测和消歧等问题并提出了相应的方法。应用这些方法,设计实现了一个藏文分词系统SegT。该系统采用格助词分块并识别临界词,然后采用最大匹配方法分词,并进行紧缩词识别。系统采用双向切分检测交集型歧义字段并使用预先统计的词频信息进行消歧。实验结果表明,该文设计的格助词分块和临界词识别方法可以将分词速度提高15%左右,但格助词分块对分词效果没有明显提高或降低。系统最终分词正确率为96.98%,基本达到了实用的水平。

SegT:A Practical Tibetan Word Segmentation System

This paper designs and implements a Tibetan word segmentation system named "SegT".It identifies critical words with a fast algorithm based on the trie structure when it segments each Tibetan sentence to blocks with case-auxiliary words.Then,it identifies abbreviated words when it segments each block to words by maximum matching.Finally,it detects ambiguities by bidirectional segmentation,and solve them by word frequency.Experiments show that it improves the segmenting speed by about 15% after applying the block segmentation method based on case-auxiliary words,but the block segmentation doesn’t significantly increase or decrease the precision.The precision of the system reaches 96.98%,which shows that it’s a practical system.